How to Implement Big Data Analytics in your Fintech Applications

In the past few years, the financial technology industry has exploded in popularity. This industry has seen a 67 percent increase in growth in a short amount of time.

This sudden uptick in the popularity of financial technology has been motivated by increased consumer awareness and trust in this type of technology. These days, more people entrust their money to third parties rather than traditional financial institutions.

More and more startups are focusing their efforts on creating financial technology. This means that the competition in this market is growing substantially.

Finding out what type of products to offer consumers is easy when doing things like:

Mining data from various sources and organizing it.

Using data to comprehend what consumer behaviors are and how to predict where the market is going.

In order to collect this data, you will have to learn how to incorporate the right systems within in your financial technology app.

Big Data Analytics Can Improve Customer Service

Letting lots of data accumulate within your app without analyzing and using it is foolish. Merely collecting data does your company a disservice and will usually lead to you losing your competitive edge.

Finding a program that will help you both collect and analyze user data is essential. With this information, you can see where the ball is being dropped in relation to your customer service. Fixing these issues will not only make your financial tech app stronger, it will allow you to serve your customers better as well.

One of the biggest trends in the world of financial technology is wealth management apps. These apps are usually far more transparent and easy to use than the wealth management tools used by large financial institutions.

These days, large wealth management firms are starting to leverage big data to keep their clients happy. Using the data from an app can help wealth management professionals develop customer profiles with high levels of accuracy. These profiles can be used to target marketing efforts and attract new clients with ease.

Not only can these data be used to acquire new customers, it can also be used to keep current clients loyal. Being able to crunch your client’s data can help you see what financial goals they are most interested in tackling. Approaching clients with information about retirement plans or new investments when they are the most interested can help you increase the amount of revenue your wealth management company brings in.

Predictive Analytics Can Reduce Fraud Risks Substantially

When it comes to data security, financial software and apps are held to a higher standard. If your company offers loans or even debt management services, you need to find a way protect yourself from fraudulent clients.

The best way to do this is by training your app with historical data. Providing the app information regarding what distinguishes a normal transaction from one that is fraudulent is key. With this information, your app will be able to use predictive analysis to detect and flag fraudulent activity.

In order to utilize the power of big data in your financial tech, you will have to work with the right professionals. A knowledgeable developer will have no problem bringing your vision of the perfect app to life.

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The Fintech Times is the world’s first and only newspaper dedicated to fintech. Published monthly, The Fintech Times explores the explosive world of financial technology, blending first hand insight, opinion and expertise with observational journalism to provide a balanced and comprehensive perspective of this rapidly evolving industry.